You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

93 lines
3.5 KiB

2 weeks ago
import asyncio
import os
import shutil
from raganything import RAGAnything, RAGAnythingConfig
from Util.RagUtil import create_llm_model_func, create_vision_model_func, create_embedding_func
import logging
# 在程序开始时添加以下配置
logging.basicConfig(
level=logging.INFO, # 设置日志级别为INFO
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
# 或者如果你想更详细地控制日志输出
logger = logging.getLogger('lightrag')
logger.setLevel(logging.INFO)
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
logger.addHandler(handler)
async def main():
# 要处理的文件路径
2 weeks ago
file_path = "Docx/《动能定理》巩固练习.docx"
WORKING_DIR = "../../Topic/MathOcr"
2 weeks ago
# 删除output目录下的所有文件
2 weeks ago
output_dir = "../../output"
2 weeks ago
shutil.rmtree(output_dir, ignore_errors=True)
os.makedirs(output_dir, exist_ok=True)
# 删除WORKING_DIR下的所有文件
shutil.rmtree(WORKING_DIR, ignore_errors=True)
os.makedirs(WORKING_DIR, exist_ok=True)
# 指定最终的索引生成目录,启动索引生成
config = RAGAnythingConfig(
working_dir=WORKING_DIR,
mineru_parse_method="auto",
enable_image_processing=True, # 处理图片
enable_table_processing=True, # 处理表格
enable_equation_processing=True, # 处理公式
)
# 自定义的大模型函数
llm_model_func = create_llm_model_func()
# 自定义的可视模型函数
vision_model_func = create_vision_model_func(llm_model_func)
# 自定义的嵌入函数
embedding_func = create_embedding_func()
rag = RAGAnything(
config=config,
llm_model_func=llm_model_func,
vision_model_func=vision_model_func,
embedding_func=embedding_func,
)
await rag.process_document_complete(
file_path=file_path,
output_dir=output_dir,
parse_method="auto",
# MinerU特殊参数 - 支持的所有kwargs
lang="ch", # 文档语言优化(如:"ch", "en", "ja"
# device="cuda:0", # 推理设备:"cpu", "cuda", "cuda:0", "npu", "mps"
# start_page=0, # 起始页码0为基准适用于PDF
# end_page=10, # 结束页码0为基准适用于PDF
formula=True, # 启用公式解析
table=True, # 启用表格解析
backend="pipeline", # 解析后端:"pipeline", "vlm-transformers"等
source="local", # 模型源:"huggingface", "modelscope", "local"
# RAGAnything标准参数
display_stats=True, # 显示内容统计信息
split_by_character=None, # 可选的文本分割字符
doc_id=None, # 可选的文档ID
)
2 weeks ago
"""
修正一下MinerU生成的Latex中如果是数字加圆圈的样式 \textcircled{1}无法在Typora或者PyCharm中显示的问题,改成兼容性更强的 \enclose{circle}{1}
"""
finalName = r'D:\dsWork\dsProject\dsRagAnything\output\《动能定理》巩固练习\auto\《动能定理》巩固练习.md'
with open(finalName, 'r', encoding='utf-8') as f:
content = f.read()
2 weeks ago
content = content.replace(r'\textcircled', r'\enclose{circle}')
2 weeks ago
with open(finalName, 'w', encoding='utf-8') as f:
f.write(content)
2 weeks ago
if __name__ == "__main__":
asyncio.run(main())